Procedural Generation Of Skill Trees In Video Games Using Graph Grammer

This study investigated the possibility of procedural generation of skill trees which are similar to skill trees in contemporary video games. A set of randomly-selected skill trees from contemporary video games, from differ- ent game genres, was compiled, and an analysis was performed to extract relevant observations from the set. Using the observations, models for skill tree generation, and for skill tree comparison were proposed, and they were followed for the generation and analysis of the results. It was found that the method of Graph Grammars provided satisfying results compared to the set of skill trees from video games. Additionally, the other methods researched, L-Systems and Naive Randomized Graph Generation, while both may still require improvements discussed in the thesis in order to provide more satis- fying results, they may still be used for particular needs by game designers as they are.